Software Engineer - risklab

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Qualifikationen

• Good understanding of microservices architecture and related design patterns, including service boundaries, resilience, observability, service-to-service communication and data ownership.
• Good knowledge of cloud-native application development, preferably on Microsoft Azure.
• Good understanding of testing strategies for production systems, including unit, integration, contract, end-to-end, performance and non-functional testing automation.
• Knowledge of Azure Data Factory, Azure Databricks, Azure Data Lake, Azure SQL, relational databases and NoSQL/cache technologies such as Redis is beneficial.
• Awareness of secure software development practices, vulnerability management and secure-by-design engineering principles.
• Strong analytical and problem-solving skills, with the ability to make pragmatic trade-offs between delivery, quality, security and maintainability.
• Comfortable working with production issues and supporting day-to-day platform operations.
• Collaborative, proactive and self-reliant working style, with the ability to communicate technical trade-offs clearly to both technical and business stakeholders.
• Proficiency in written and spoken English.

Erfahrung

• 3 to 5 years of professional experience in software development, ideally in backend, API, cloud-native or platform engineering roles.
• Strong hands-on experience designing and implementing REST APIs, including API lifecycle management, versioning strategies, contract design, backwards compatibility, authentication, authorisation and documentation.
• Hands-on experience with at least one modern programming language, ideally Python or C#.
• Hands-on experience with Docker and Kubernetes. Azure Kubernetes Service (AKS) and Helm experience are strong advantages.
• Practical experience with CI/CD pipelines and DevOps practices. GitHub Actions experience is preferred and exposure to DevSecOps practices is highly beneficial.
• Experience improving production systems in areas such as scalability, performance, monitoring, incident troubleshooting, vulnerability remediation and operational reliability.
• Interest in investment technology, quantitative methods, optimisation, analytics, AI-assisted software development, agentic AI systems, or portfolio construction is a plus; prior finance experience is not required.

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